Proteogenomic characterization of human colon and rectal cancer

Bing Zhang; Jing Wang; Xiaojing Wang; Jing Zhu; Qi Liu; Zhiao Shi; Matthew C. Chambers; Lisa J. Zimmerman; Kent F. Shaddox; Sangtae Kim; Sherri R. Davies; Sean Wang; Pei Wang; Christopher R. Kinsinger; Robert C. Rivers; Henry Rodriguez; R. Reid Townsend; Matthew J.C. Ellis; Steven A. Carr; David L. Tabb; Robert J. Coffey; Robbert J.C. Slebos; Daniel C. Liebler; Michael A. Gillette; Karl R. Klauser; Eric Kuhn; D. R. Mani; Philipp Mertins; Karen A. Ketchum; Amanda G. Paulovich; Jeffrey R. Whiteaker; Nathan J. Edwards; Peter B. McGarvey; Subha Madhavan; Daniel Chan; Akhilesh Pandey; Ie Ming Shih; Hui Zhang; Zhen Zhang; Heng Zhu; Gordon A. Whiteley; Steven J. Skates; Forest M. White; Douglas A. Levine; Emily S. Boja; Tara Hiltke; Mehdi Mesri; Kenna M. Shaw; Stephen E. Stein; David Fenyo; Tao Liu; Jason E. McDermott; Samuel H. Payne; Karin D. Rodland; Richard D. Smith; Paul Rudnick; Michael Snyder; Yingming Zhao; Xian Chen; David F. Ransohoff; Andrew N. Hoofnagle; Melinda E. Sanders; Yue Wang; Li Ding

doi:10.1038/nature13438

Proteogenomic characterization of human colon and rectal cancer

Bing Zhang, Jing Wang, Xiaojing Wang, Jing Zhu, Qi Liu, Zhiao Shi, Matthew C. Chambers, Lisa J. Zimmerman, Kent F. Shaddox, Sangtae Kim, Sherri R. Davies, Sean Wang, Pei Wang, Christopher R. Kinsinger, Robert C. Rivers, Henry Rodriguez, R. Reid Townsend, Matthew J.C. Ellis, Steven A. Carr, David L. TabbRobert J. Coffey, Robbert J.C. Slebos, Daniel C. Liebler, Michael A. Gillette, Karl R. Klauser, Eric Kuhn, D. R. Mani, Philipp Mertins, Karen A. Ketchum, Amanda G. Paulovich, Jeffrey R. Whiteaker, Nathan J. Edwards, Peter B. McGarvey, Subha Madhavan, Daniel Chan, Akhilesh Pandey, Ie Ming Shih, Hui Zhang, Zhen Zhang, Heng Zhu, Gordon A. Whiteley, Steven J. Skates, Forest M. White, Douglas A. Levine, Emily S. Boja, Tara Hiltke, Mehdi Mesri, Kenna M. Shaw, Stephen E. Stein, David Fenyo, Tao Liu, Jason E. McDermott, Samuel H. Payne, Karin D. Rodland, Richard D. Smith, Paul Rudnick, Michael Snyder, Yingming Zhao, Xian Chen, David F. Ransohoff, Andrew N. Hoofnagle, Melinda E. Sanders, Yue Wang, Li Ding

Laboratory Medicine and Pathology

Research output: Contribution to journal › Article › peer-review

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Abstract

Extensive genomic characterization of human cancers presents the problem of inference from genomic abnormalities to cancer phenotypes. To address this problem, we analysed proteomes of colon and rectal tumours characterized previously by The Cancer Genome Atlas (TCGA) and perform integrated proteogenomic analyses. Somatic variants displayed reduced protein abundance compared to germline variants. Messenger RNA transcript abundance did not reliably predict protein abundance differences between tumours. Proteomics identified five proteomic subtypes in the TCGA cohort, two of which overlapped with the TCGA 'microsatellite instability/CpG island methylation phenotype' transcriptomic subtype, but had distinct mutation, methylation and protein expression patterns associated with different clinical outcomes. Although copy number alterations showed strong cis- and trans-effects on mRNA abundance, relatively few of these extend to the protein level. Thus, proteomics data enabled prioritization of candidate driver genes. The chromosome 20q amplicon was associated with the largest global changes at both mRNA and protein levels; proteomics data highlighted potential 20q candidates, including HNF4A (hepatocyte nuclear factor 4, alpha), TOMM34 (translocase of outer mitochondrial membrane 34) and SRC (SRC proto-oncogene, non-receptor tyrosine kinase). Integrated proteogenomic analysis provides functional context to interpret genomic abnormalities and affords a new paradigm for understanding cancer biology.

Original language	English (US)
Pages (from-to)	382-387
Number of pages	6
Journal	Nature
Volume	513
Issue number	7518
DOIs	https://doi.org/10.1038/nature13438
State	Published - Sep 18 2014

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Zhang, B., Wang, J., Wang, X., Zhu, J., Liu, Q., Shi, Z., Chambers, M. C., Zimmerman, L. J., Shaddox, K. F., Kim, S., Davies, S. R., Wang, S., Wang, P., Kinsinger, C. R., Rivers, R. C., Rodriguez, H., Townsend, R. R., Ellis, M. J. C., Carr, S. A., ... Ding, L. (2014). Proteogenomic characterization of human colon and rectal cancer. Nature, 513(7518), 382-387. https://doi.org/10.1038/nature13438

Zhang, B, Wang, J, Wang, X, Zhu, J, Liu, Q, Shi, Z, Chambers, MC, Zimmerman, LJ, Shaddox, KF, Kim, S, Davies, SR, Wang, S, Wang, P, Kinsinger, CR, Rivers, RC, Rodriguez, H, Townsend, RR, Ellis, MJC, Carr, SA, Tabb, DL, Coffey, RJ, Slebos, RJC, Liebler, DC, Gillette, MA, Klauser, KR, Kuhn, E, Mani, DR, Mertins, P, Ketchum, KA, Paulovich, AG, Whiteaker, JR, Edwards, NJ, McGarvey, PB, Madhavan, S, Chan, D, Pandey, A, Shih, IM, Zhang, H, Zhang, Z, Zhu, H, Whiteley, GA, Skates, SJ, White, FM, Levine, DA, Boja, ES, Hiltke, T, Mesri, M, Shaw, KM, Stein, SE, Fenyo, D, Liu, T, McDermott, JE, Payne, SH, Rodland, KD, Smith, RD, Rudnick, P, Snyder, M, Zhao, Y, Chen, X, Ransohoff, DF, Hoofnagle, AN, Sanders, ME, Wang, Y & Ding, L 2014, 'Proteogenomic characterization of human colon and rectal cancer', Nature, vol. 513, no. 7518, pp. 382-387. https://doi.org/10.1038/nature13438

@article{f3e6208c197f461f9620f82c62a4f682,

title = "Proteogenomic characterization of human colon and rectal cancer",

abstract = "Extensive genomic characterization of human cancers presents the problem of inference from genomic abnormalities to cancer phenotypes. To address this problem, we analysed proteomes of colon and rectal tumours characterized previously by The Cancer Genome Atlas (TCGA) and perform integrated proteogenomic analyses. Somatic variants displayed reduced protein abundance compared to germline variants. Messenger RNA transcript abundance did not reliably predict protein abundance differences between tumours. Proteomics identified five proteomic subtypes in the TCGA cohort, two of which overlapped with the TCGA 'microsatellite instability/CpG island methylation phenotype' transcriptomic subtype, but had distinct mutation, methylation and protein expression patterns associated with different clinical outcomes. Although copy number alterations showed strong cis- and trans-effects on mRNA abundance, relatively few of these extend to the protein level. Thus, proteomics data enabled prioritization of candidate driver genes. The chromosome 20q amplicon was associated with the largest global changes at both mRNA and protein levels; proteomics data highlighted potential 20q candidates, including HNF4A (hepatocyte nuclear factor 4, alpha), TOMM34 (translocase of outer mitochondrial membrane 34) and SRC (SRC proto-oncogene, non-receptor tyrosine kinase). Integrated proteogenomic analysis provides functional context to interpret genomic abnormalities and affords a new paradigm for understanding cancer biology.",

author = "Bing Zhang and Jing Wang and Xiaojing Wang and Jing Zhu and Qi Liu and Zhiao Shi and Chambers, {Matthew C.} and Zimmerman, {Lisa J.} and Shaddox, {Kent F.} and Sangtae Kim and Davies, {Sherri R.} and Sean Wang and Pei Wang and Kinsinger, {Christopher R.} and Rivers, {Robert C.} and Henry Rodriguez and Townsend, {R. Reid} and Ellis, {Matthew J.C.} and Carr, {Steven A.} and Tabb, {David L.} and Coffey, {Robert J.} and Slebos, {Robbert J.C.} and Liebler, {Daniel C.} and Gillette, {Michael A.} and Klauser, {Karl R.} and Eric Kuhn and Mani, {D. R.} and Philipp Mertins and Ketchum, {Karen A.} and Paulovich, {Amanda G.} and Whiteaker, {Jeffrey R.} and Edwards, {Nathan J.} and McGarvey, {Peter B.} and Subha Madhavan and Daniel Chan and Akhilesh Pandey and Shih, {Ie Ming} and Hui Zhang and Zhen Zhang and Heng Zhu and Whiteley, {Gordon A.} and Skates, {Steven J.} and White, {Forest M.} and Levine, {Douglas A.} and Boja, {Emily S.} and Tara Hiltke and Mehdi Mesri and Shaw, {Kenna M.} and Stein, {Stephen E.} and David Fenyo and Tao Liu and McDermott, {Jason E.} and Payne, {Samuel H.} and Rodland, {Karin D.} and Smith, {Richard D.} and Paul Rudnick and Michael Snyder and Yingming Zhao and Xian Chen and Ransohoff, {David F.} and Hoofnagle, {Andrew N.} and Sanders, {Melinda E.} and Yue Wang and Li Ding",

year = "2014",

month = sep,

day = "18",

doi = "10.1038/nature13438",

language = "English (US)",

volume = "513",

pages = "382--387",

journal = "Nature",

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TY - JOUR

T1 - Proteogenomic characterization of human colon and rectal cancer

AU - Zhang, Bing

AU - Wang, Jing

AU - Wang, Xiaojing

AU - Zhu, Jing

AU - Liu, Qi

AU - Shi, Zhiao

AU - Chambers, Matthew C.

AU - Zimmerman, Lisa J.

AU - Shaddox, Kent F.

AU - Kim, Sangtae

AU - Davies, Sherri R.

AU - Wang, Sean

AU - Wang, Pei

AU - Kinsinger, Christopher R.

AU - Rivers, Robert C.

AU - Rodriguez, Henry

AU - Townsend, R. Reid

AU - Ellis, Matthew J.C.

AU - Carr, Steven A.

AU - Tabb, David L.

AU - Coffey, Robert J.

AU - Slebos, Robbert J.C.

AU - Liebler, Daniel C.

AU - Gillette, Michael A.

AU - Klauser, Karl R.

AU - Kuhn, Eric

AU - Mani, D. R.

AU - Mertins, Philipp

AU - Ketchum, Karen A.

AU - Paulovich, Amanda G.

AU - Whiteaker, Jeffrey R.

AU - Edwards, Nathan J.

AU - McGarvey, Peter B.

AU - Madhavan, Subha

AU - Chan, Daniel

AU - Pandey, Akhilesh

AU - Shih, Ie Ming

AU - Zhang, Hui

AU - Zhang, Zhen

AU - Zhu, Heng

AU - Whiteley, Gordon A.

AU - Skates, Steven J.

AU - White, Forest M.

AU - Levine, Douglas A.

AU - Boja, Emily S.

AU - Hiltke, Tara

AU - Mesri, Mehdi

AU - Shaw, Kenna M.

AU - Stein, Stephen E.

AU - Fenyo, David

AU - Liu, Tao

AU - McDermott, Jason E.

AU - Payne, Samuel H.

AU - Rodland, Karin D.

AU - Smith, Richard D.

AU - Rudnick, Paul

AU - Snyder, Michael

AU - Zhao, Yingming

AU - Chen, Xian

AU - Ransohoff, David F.

AU - Hoofnagle, Andrew N.

AU - Sanders, Melinda E.

AU - Wang, Yue

AU - Ding, Li

PY - 2014/9/18

Y1 - 2014/9/18

N2 - Extensive genomic characterization of human cancers presents the problem of inference from genomic abnormalities to cancer phenotypes. To address this problem, we analysed proteomes of colon and rectal tumours characterized previously by The Cancer Genome Atlas (TCGA) and perform integrated proteogenomic analyses. Somatic variants displayed reduced protein abundance compared to germline variants. Messenger RNA transcript abundance did not reliably predict protein abundance differences between tumours. Proteomics identified five proteomic subtypes in the TCGA cohort, two of which overlapped with the TCGA 'microsatellite instability/CpG island methylation phenotype' transcriptomic subtype, but had distinct mutation, methylation and protein expression patterns associated with different clinical outcomes. Although copy number alterations showed strong cis- and trans-effects on mRNA abundance, relatively few of these extend to the protein level. Thus, proteomics data enabled prioritization of candidate driver genes. The chromosome 20q amplicon was associated with the largest global changes at both mRNA and protein levels; proteomics data highlighted potential 20q candidates, including HNF4A (hepatocyte nuclear factor 4, alpha), TOMM34 (translocase of outer mitochondrial membrane 34) and SRC (SRC proto-oncogene, non-receptor tyrosine kinase). Integrated proteogenomic analysis provides functional context to interpret genomic abnormalities and affords a new paradigm for understanding cancer biology.

AB - Extensive genomic characterization of human cancers presents the problem of inference from genomic abnormalities to cancer phenotypes. To address this problem, we analysed proteomes of colon and rectal tumours characterized previously by The Cancer Genome Atlas (TCGA) and perform integrated proteogenomic analyses. Somatic variants displayed reduced protein abundance compared to germline variants. Messenger RNA transcript abundance did not reliably predict protein abundance differences between tumours. Proteomics identified five proteomic subtypes in the TCGA cohort, two of which overlapped with the TCGA 'microsatellite instability/CpG island methylation phenotype' transcriptomic subtype, but had distinct mutation, methylation and protein expression patterns associated with different clinical outcomes. Although copy number alterations showed strong cis- and trans-effects on mRNA abundance, relatively few of these extend to the protein level. Thus, proteomics data enabled prioritization of candidate driver genes. The chromosome 20q amplicon was associated with the largest global changes at both mRNA and protein levels; proteomics data highlighted potential 20q candidates, including HNF4A (hepatocyte nuclear factor 4, alpha), TOMM34 (translocase of outer mitochondrial membrane 34) and SRC (SRC proto-oncogene, non-receptor tyrosine kinase). Integrated proteogenomic analysis provides functional context to interpret genomic abnormalities and affords a new paradigm for understanding cancer biology.

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JO - Nature

JF - Nature

IS - 7518

ER -

Proteogenomic characterization of human colon and rectal cancer

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